Maximizing throughput for optical burst switching networks

A key problem in Optical Burst Switching (OBS) is to schedule as many bursts as possible on wavelength channels so that the throughput is maximized and the burst loss is minimized. Currently, most of the research on OBS (e.g., burst scheduling and assembly algorithms) has been concentrated on reducing burst loss in an "average-case" sense. Little effort has been devoted to understanding the worst-case performance. Since OBS itself is an open-loop control system, it may often exhibit a worst-case behavior when adversely synchronized, thus a poor worst-case performance can lead to an unacceptable system-wide performance. In this paper, we use competitive analysis to analyze the worst-case performance of a large set of scheduling algorithms called best-effort online scheduling algorithms, for OBS networks, and establish a number of interesting upper and lower bounds on the performance of such algorithms. Our analysis shows that the performance of any best-effort online algorithm is closely related to a few factors, such as the range of offset time, burst length ratio, scheduling algorithm, and number of data channels. A surprising discovery is that the worst-case performance of any best-effort online scheduling algorithm is primarily determined by the maximum to minimum burst length ratio, followed by the range of offset time. Furthermore, if all bursts have the same burst length and offset time, all best-effort online scheduling algorithms generate the same optimal solution, regardless how different they may look like. Our analysis can also be extended to some non-best-effort online scheduling algorithms, such as the well-known Horizon algorithm, and establish similar bounds. Based on the analytic results, we give guidelines for several widely discussed OBS problems, including burst assembly, offset time setting and scheduling algorithm design, and propose a new channel reservation protocol called VFO to improve the worst-case performance. Our simulation shows that it is quite often for an online scheduling algorithm to exhibit its (near) worst-case performance. Thus improving the worst-case performance is essential. Our simulation also suggests that VFO reduces the average burst loss rate by as much as 35%.